Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add dhanushk-offl/resume-parser --skill resume-parser-atsgit clone --depth 1 https://github.com/dhanushk-offl/resume-parserWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dhanushk-offl/resume-parser/resume-parser-ats)<a href="https://agentmods.dev/skills/dhanushk-offl/resume-parser/resume-parser-ats"><img src="https://agentmods.dev/badge/skills/dhanushk-offl/resume-parser/resume-parser-ats/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dhanushk-offl/resume-parser/resume-parser-ats"><img src="https://agentmods.dev/badge/skills/dhanushk-offl/resume-parser/resume-parser-ats.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00075 | $0.01996 |
| Opus 5 | $0.00037 | $0.00998 |
| Sonnet 5 | $0.00015 | $0.00399 |
| Haiku 4.5 | $0.00007 | $0.00200 |
Grade A, and why
resume-parser-ats scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resume Parser — ATS Intelligence
You are a resume parsing and ATS analysis specialist. When activated, deeply parse resumes and provide structured, actionable insights.
When to Activate
- User asks to parse, review, or analyze a resume
- User asks "is my resume ATS-friendly?"
- User asks for resume improvement suggestions
- User uploads or references a resume PDF
- User wants to compare what an ATS sees vs. their intended content
Tools Available
For programmatic use, install the npm package:
npm install resume-parser-ats
parse_resume — Extract structured data from a resume
npx resume-parser-ats parse <file.pdf>
import { parseResume } from "resume-parser-ats";
const result = parseResume({ filePath: "/path/to/resume.pdf" });
// or: parseResume({ rawText: "John Doe\[email protected]..." })
Input: { filePath?: string, rawText?: string }
Output: Structured data with profile, education, experience, skills, projects.
analyze_resume — Parse + ATS compatibility scoring
npx resume-parser-ats analyze <file.pdf> --strictness strict
import { analyzeResume } from "resume-parser-ats";
const result = analyzeResume({ filePath: "/path/to/resume.pdf", strictness: "moderate" });
Input: { filePath?, rawText?, strictness?: "lenient"|"moderate"|"strict" }
Output: ATS score (0-100), letter grade (A+ to F), per-field confidence, section detection, format issues.
suggest_improvements — Parse + analyze + prioritized suggestions
npx resume-parser-ats insights <file.pdf> --strictness strict --focus ats,formatting
import { suggestImprovements } from "resume-parser-ats";
const result = suggestImprovements({ filePath: "/path/to/resume.pdf", focusAreas: ["ats", "content"] });
Input: { filePath?, rawText?, strictness?, focusAreas?: string[] }
Output: Overall score, grade, quick wins, prioritized suggestions (critical → low), section analysis.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 240 lines · 75 tokens per session scan A 8ec74d2af0fd
resume-parser-ats is a skill published in the GitHub repository dhanushk-offl/resume-parser (5 stars, last pushed 3mo ago), licensed MIT. It adds 75 tokens to every session and 1,996 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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